Concurrent Viewers Research Articles

DART: Latest results from the Dimorphos impact and a look forward to future planetary defense initiatives

DART, the Double Asteroid Redirection Test, successfully impacted asteroid Dimorphos on September 26, 2022, becoming the first mission to demonstrate asteroid deflection. Shared live via a NASA broadcast, over a million concurrent viewers around the world watched as the DART spacecraft streamed images to Earth up to the final second before its impact with Dimorphos. In this paper, we share the final phases of the DART encounter and the latest results from the DART Investigation Team's analysis of ground and space-based data. This includes measurements on the amount of deflection that DART imparted on Dimorphos, a determination of the momentum transfer enhancement factor, and results on understanding the geology and surface characteristics of the impact site. The success of the DART mission paves the future for a bold international Planetary Defense program. We also share ideas on bolstering international coordination, developing new technologies that can mitigate different types of asteroid threats, and closing identified gaps in our overall preparedness.

Students Report of ACM Multimedia System 2021

The 12th ACM Multimedia Systems Conference (MMSys'21) happened from September 28th through October 1st, 2021. The MMSys conference is an important forum for researchers in multimedia systems. But, due to the ongoing pandemic, the event was held in a hybrid mode - onsite in Istanbul, Turkey, and online. Organizers and chairs (Özgü Alay, Cheng-Hsin Hsu, and Ali C. Begen) worked very hard to make sure the conference was successful, both for the on-site participants (around 50) and the online participants (with a peak of 330 concurrent viewers). For a small description of the event, take a look at the text written by Ali Begen, one of the general chairs. To encourage student authors to participate on-site, SIGMM has sponsored a group of students with Student Travel Grant Awards. Students who wanted to apply for this travel grant needed to submit an online form before the submission deadline. Then, the selection committee chose 7 travel grant winners. The selected students received either 1,000 or 2,000 USD to cover their airline tickets as well accommodation costs for this event. We asked the travel grant winners to share their unique experiences attending MMSys'21. The following are their comments.

SAT-485 NEW METHODS OF CONFERENCE COVERAGE ON SOCIAL MEDIA –DO THEY HELP INCREASE THE REACH?

Over the past decade, there is an increase in the utilization of various Social Media (SoMe) platforms in disseminating & sharing information from medical conferences. Twitter’s popularity among nephrologists for this purpose is widespread. At the World Congress of Nephrology (WCN) in Mexico in April 2017, a SoMe Task Force was created by the International Society of Nephrology (ISN). One of the main objectives of this was a comprehensive coverage of the lectures & presentations shared via different SoMe platforms. In a similar manner, an ISN WCN SoMe Team was created to cover the World Congress of Nephrology in Melbourne in April 2019 to disseminate scientific info from the conference. The ISN WCN SoMe Team launched Poster Talks (PTs), where the Author gives a voice over describing the poster. Also, Visual Abstracts (VA) of posters/oral papers & live talks (Live VAs) were created. Interviews of speakers & poster presenters as well as live stream of late breaking clinical trial (LBCT) were additional distinctive methods adopted. This was the first time Facebook was used to extend an international nephrology conference’s reach & its own analytics were used. Twitter analysis of these newer methods were done using Symplur & NOD Analytics. Periscope and YouTube data was analyzed looking at interviews & how they impacted on information spread. Over 17000 tweets from the conference were accessed in 90 countries (see figure 1). There were 1943 unique participants. There were 34 video interviews - 25 poster interviews & 9 speaker interviews. An index for the quantity of education delivered during these interviews was created (see figure 2). 21 Poster Talks and 29 VAs were created, (21 poster VAs & 8 Live VAs). When compared, these new methods of coverage were accessed, retweeted and commented upon more frequently than traditional slide-based tweets. YouTube data analysis showed 696 unique viewers and 824 min watch time. Highest attention span was of 3:21. Facebook data analysis showed that the Social Media reach was 340K, with 1786 interactions, 30 shares & 1720 likes. Live stream data of LBCT showed 2713 playbacks with 587 peak concurrent viewers, 798 hours of total view time with an average session length of 17.6 min with participants from 59 countries tuning in, generating a volume of more than 7000 tweets.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The newer methods of Social Media information dissemination from Conferences namely Poster Talks, Interviews, Visual Abstracts, Late Breaking Clinical Trials - Live streams as well as adding Facebook and & Youtube as platforms of sharing, helped increase the interaction and & reach of the conference to a significant extent.

A Multi-Commodity Flow Problem for Fair Resource Allocation in Multi-Path Video Delivery Networks

Video streaming services employ the Internet to distribute content to an ever-increasing number of concurrent viewers. The delivery architecture employed by leading video platforms requires players to run a control algorithm dynamically choosing the video bitrate to match the time-varying network bandwidth and avoid playback interruptions due to buffer underruns. Such an algorithm is generally designed to (selfishly) improve the quality individually perceived by users. Consequently, this control architecture leads, in the optimal case, to maximize the average quality perceived collectively by all users and not to a distribution of resources that is fair in terms of user perceived quality. We argue that video service providers should manage their delivery network to address fairness issues to gracefully degrade the perceived quality equally for all users when resources become scarce. Even though the general problem of providing a fair level of perceived quality does not scale with the cumbersome number of concurrent users, this paper shows that the Multi-Commodity Flow Problem (MCFP) optimization framework is a proper and efficient tool to address this open issue. First, we show how to cast the resource allocation problem to an MCFP and then we propose a strategy to make the resulting problem tractable for video distribution platforms serving massive audiences. The performance of the proposed optimal fair resource allocation strategy is assessed using realistic simulations involving thousands of concurrent video sessions on a real network topology by varying both the total load on the network and key system parameters.

Detecting Cheating in Computer Games using Data Mining Methods

Cheating is prevalent in the gaming industry and is causing several types of uproars. Counter-Strike is a popular franchise which has had up to peaks of 850 thousand players at once playing. Professional events such as ESL One Cologne 2015 had 1.3 million concurrent viewers. Video games are a huge industry, sadly, integrity of the players is lacking. Professional players have been found to be using cheats at events, and cheaters in casual matches are expected to be found regularly. Current anti-cheat systems may use signature-based approaches and even heuristics, but none of them have explicitly stated to be using data mining techniques. Although signature methods may catch a lot of not technically adept cheaters, the ones we need worry about are the ones using metamorphic or polymorphic cheats that stay undetectable to these systems. To detect these kinds of cheats, another method needs to be put in place. Data mining techniques used for detecting zero-day malware as well as player behaviorbased techniques for detecting cheaters are discussed in this proposal. The results of these methods are promising and will hopefully rid the gaming industry of ill-minded players.

Interest-suppression-based NDN live video broadcasting over wireless LAN

Named data networking (NDN) is a new Internet architecture that replaces today’s focus on where – addresses and hosts with what – the content that users and applications care about. One of NDN’s prominent advantages is scalable and efficient content distribution due to its native support of caching and multicast in the network. However, at the last hop to wireless users, often the WiFi link, current NDN implementation still treats the communication as multiple unicast sessions, which will cause duplicate packets and waste of bandwidth when multiple users request for the same popular content. WiFi’s built-in broadcast mechanism can alleviate this problem, but it suffers from packet loss since there is no MAC-layer acknowledgement as in unicast. In this paper, we develop a new NDN-based cross-layer approach called NLB for efficient and scalable live video streaming over wireless LAN. The core ideas are: using WiFi’s broadcast channel to deliver content from the access point to the users, a leader-based mechanism to suppress duplicate requests from users, and receiver-driven rate control and loss recovery. The design is implemented and evaluated in a physical testbed comprised of one software AP and 20 Raspberry Pi-based WiFi clients. While NDN with multiple unicast sessions or plain broadcast can support no more than ten concurrent viewers of a 1Mbps streaming video, NDN plus NLB supports all 20 viewers, and Received December 29, 2015; accepted April 28, 2016 E-mail: zhxp@tsinghua.edu.cn can likely support much more when present.

Did the Super Bowl Kill the Internet?

Given the rapid increase in Internet streaming services to access multimedia content, to the detriment of traditional cable, satellite, and terrestrial, it is to be expected that this traffic will affect the performance of the Internet at several levels. One such level is the communication between autonomous systems that is primarily based on border gateway protocol (BGP). In order to understand this impact, a tool was developed to detect the problems that occur during a specific time period. This tool is able to identify and classify flapping events providing information about the networks potentially involved in the disruptions. The main focus of this paper is the analysis of the BGP updates registered during Super Bowl 2016 in order to understand how a large streaming event affects the Internet at the BGP level. Those results show that an increase in the number of updates happened during key times when a large number of concurrent viewers connected to the game. Many dampening and flapping events were observed accordingly. From those events, networks potentially affected were detected and categorized. The results of our study suggest that the Internet is not prepared to accommodate the potential streaming traffic generated during major events. This is of utmost importance for content providers and content delivery networks in designing their broadcast strategies which should take into consideration not only the scalability of their own servers but also the way in which data reaches the viewer.

Holistic modelling, simulation and visualisation of demand and supply chains

The evolution of the economic and technological contexts pressure businesses toward transforming their demand and supply chains to become more customer–centric, collaborative, innovation enabling, agile and personalised. Simulation models are needed to contrast actual vs. proposed chains, analyse the dynamic performance of these chains, and understand their overall behaviour in specific contexts. This paper proposes a holistic agent–oriented approach for modelling, simulation and visualisation of such demand and supply chains. The simulation platform for extended enterprises (SPEE) developed exploits multiple concurrent viewers that can both illustrate global multi–perspective insights into the supply chain as well as tunnel down to highly detailed information. This allows decision makers to embed themselves into the simulation and obtain the holistic visualisation needed to support their decisions.

Estimation of Worst-Case Bandwidth Requirements of Video-on-Demand Systems with Replica Servers using the M/G/∞ Model

This study assesses the worst-case demand and replication models for determining the bandwidth required by the origin server when a number of video programs in a video-on-demand system are replicated on replica servers. The bandwidth required by the video- on-demand system determines the number of viewers that could watch video programs simultaneously. If a video program is viewed in its entirety, the required bandwidth is estimated based on the number of concurrent viewers as well as the length of the video program. Unlike traditional research models that use the hit ratio to assess the replication benefits, this study uses the M/G/∞ model to examine the related phenomenon and problems in this field. We develop a selection model for replication using the product of the viewing request probability and the video length as the main factor in determining the videos selected for replication. This model theoretically outperforms traditional models that consider only the viewing request probability in the benefits of reducing the worst-case demand at origin server, and the simulation results validate the theoretical results. Due to resource constraints in the replica server, discussions and verifications on the optimization of the proposed replication model were carried out and the findings were used as the basis for the development of a heuristic algorithm. The results derived using this heuristic algorithm are almost the same as the optimized results derived from LINGO.

On HTTP live streaming in large enterprises

In this work, we present a distributed caching solution which addresses the problem of efficient delivery of HTTP live streams in large private networks. With our system, we have conducted tests on a number of pilot deployments. The largest of them, with 3000 concurrent viewers, consistently showed that our system saves more than 90% of traffic towards the source of the stream while providing the same quality of user experience of a CDN. Another result is that our solution was able to reduce the load on the bottlenecks in the network by an average of 91.6%.

Design and analysis of a look-ahead scheduling scheme to support pause-resume for video-on-demand applications

In a video-on-demand (VOD) system, subscribers can choose both the movie they wish to view and the time they wish to view it. In such an environment there are invariably “hot” videos which are requested by many viewers. The requirement that each viewer be able to independently pause the video at any instant and later resume the viewing with little delay can cause difficulties in batching viewers for each showing. Under batching, a single video stream is shared by multiple concurrent viewers and a resume request has to wait for additional stream capacity to become available before actual resumption can occur. The conventional approach to the support of on-demand pause-resume provides one video access stream to disks for each video request. This can greatly increase the disk arm requirements of a VOD system. In this paper, we propose a more efficient mechanism to support the pause-resume feature usinglook-ahead scheduling withlook-aside buffering. The idea is to use buffering to increase the number of concurrent viewers supportable. The concept of look-ahead scheduling is not to back up each viewer with a real stream capacity so he can pause and resume at any time, but rather with a (look-ahead) stream that is currently being used for another showing which is close to completion. Before the look-ahead stream becomes available, the pause and resume features have to be supported by the original stream through (look-aside) buffering of the missed content. It is shown via simulations that the proposed scheme can provide a substantially greater throughput than the approach without batching. Furthermore, for a given amount of buffer, the improvement in throughput grows more than linearly with the stream capacity of the server. In other words, the look-ahead stream scheduling scheme operates with good economy of scale because it is easier to form look-ahead streams for video servers with larger stream capacity.